/*
 * Javlov - a Java toolkit for reinforcement learning with multi-agent support.
 * 
 * Copyright (c) 2009 Matthijs Snel
 * 
 * This program is free software: you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation, either version 3 of the License, or
 * (at your option) any later version.
 *
 * This program is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with this program.  If not, see <http://www.gnu.org/licenses/>.
 */
package net.javlov.world.grid;

import net.javlov.Action;
import net.javlov.Agent;
import net.javlov.RewardFunction;
import net.javlov.world.Body;
import net.javlov.world.CollisionEvent;
import net.javlov.world.CollisionListener;

/**
 * Standard impl of a reward function in a gridworld. Assumes reward of -1 on every step,
 * plus any reward configured when colliding with a body such as an obstacle or the goal.
 * 
 * @author Matthijs Snel
 *
 */
public class GridRewardFunction implements CollisionListener, RewardFunction {

	protected GridWorld world;
	
	protected double reward;
	
	public GridRewardFunction(GridWorld world) {
		this.world = world;
		reward = 0;
	}
	
	@Override
	public void collisionOccurred(CollisionEvent e) {
		//TODO assuming body1 belongs to agent that is currently executing action and will
		//thus receive reward; is this valid assumption?
		reward += e.getBody2().getReward();
	}

	@Override
	public double calculateReward() {
		return reward;
	}

	@Override
	public void preAction(Action a, Agent agent) {
		reward = -1;		
	}
}
